Motion capture is used extensively in computer animation, Bruderlin et al., “Motion signal processing,” Proceedings of SIGGRAPH 95, pp. 97-104, 1995, Witkin et al, “Motion warping,” Proceedings of SIGGRAPH 95, pp. 105-108, 1995, Gleicher, “Retargetting motion to new characters,” Proceedings of SIGGRAPH 9, pp. 33-42, 1998, Kovar et al., “Motion graphs,” ACM Transactions on Graphics 21, 3, pp. 473-482, 2002, and Arikan et al., “Motion synthesis from annotations,” pp. 402-408, 2003.
Motion capture transfers expressive performances of real actors to fantastic and realistically appearing characters. An entire industry has emerged in support of these activities and numerous recordings of human performances are now available in large motion repositories.
However, conventional motion capture requires collection in a pristine studio setting. That inhibits the broader use of motion capture in natural environments. As a result, motions such as running, skiing, and driving are simply never acquired, while others such as golf swings and football games are recorded in unnatural environments, which may affect the recorded performances.
Extended hour-long theatrical performances, which could be captured by current motion capture systems, are rarely seen or recorded, because doing so requires large audience-free studios and an excessive cost. Recording everyday human motions in natural environments is not possible.
The lack of comprehensive motion data and the exclusiveness of current motion-capture systems impair advanced computer graphics, and prevent broader application of motion processing in design of intuitive user interfaces, monitoring of medical rehabilitation, and many other applications.
The success of data-driven methods is conditioned on practical availability of large and varied data sets. An inexpensive and versatile motion-capture system could contribute to the collection of large data sets orders of magnitude larger than the current motion repositories. This enhanced infrastructure could then support large-scale analysis of human motion including its style, efficiency, and adaptability.
Several motion capture systems have been described. The advantages and disadvantages are presented in several surveys, Meyer et al., “A survey of position-trackers,” Presence 1, 2, pp. 173-200, 1992, Hightower et al., “Location systems for ubiquitous computing,” IEEE Computer 34, 8, pp. 57-66, 2001, and Welch et al., “Motion tracking: No silver bullet, but a respectable arsenal, IEEE Computer Graphics and Applications, special issue on Tracking 22, 6, pp. 24-38, 2002.
Optical, electromagnetic, electromechanic, inertial, and acoustic systems are now evaluated for motion capture in natural environments.
Optical motion capture places retro-reflective markers or light emitting diodes on a body. Three-dimensional marker locations are determined using triangulation methods from the images recorded with cameras. Those systems are favored for computer animation and the film industry because of their accuracy and fast update rates. The disadvantages of that approach are cost and lack of portability.
Electromagnetic systems detect the location and orientation (pose) of each marker using the magnetic field generated by a large coil. Those systems offer good accuracy and medium update speeds. Although more portable than optical motion capture, electromagnetic systems are heavy, expensive, and consume a lot of power.
Electromechanic systems require an actor to wear an exoskeleton. In those systems, joint angles are measured directly, e.g., using electric resistance. Direct estimates of location cannot be acquired. The exoskeleton is uncomfortable and difficult to wear for extended time periods.
Inertial motion capture systems measure rotation of joint, angles using gyroscopes or accelerometers placed on each body limb. Like electromechanical systems, they cannot measure location and distances directly for applications that must sample the geometry of objects in the environment. More importantly, the measurements drift by a significant amount over extended time periods.
An acousto-inertial system for indoor tracking applications is described by Foxlin et al., “Constellation: A wide-range wireless motion-tracking system for augmented reality and virtual set application;” Proceedings of SIGGRAPH 98, pp. 371-378, 1998. That system requires a constellation of transponder beacons mounted at known, locations of a ceiling. Obviously, that system is not mobile, and cannot be used outdoors.
In the Bat system, an ultrasonic emitter is worn by a user and receivers are placed at fixed locations in the environment. Ward et al., “A new location technique for the active office,” IEEE Personal Communications 4, 5, pp. 42-47, 1997. The emitter sends an ultrasonic pulse when triggered by an RF signal from a central system.
The Cricket location system employs a number of ultrasonic beacons placed in the environment, Priyantha et al., “The cricket location-support system,” Proceedings of the 6th Annual ACM International Conference on Mobile Computing and Networking (MobiCom '00), 2000. The beacons send ultrasonic pulses along with RF signals at random times in order to minimize possible signal interference. That allows multiple receivers to be localized independently. A similar system is described by Randell et al., “Low cost indoor positioning system,” Ubicomp 2001: Ubiquitous Computing, pp. 42-48, 2001. The main difference in the latter system is that the beacons are connected to a central controller that sends RF synchronization signals to the receivers and orders the beacons to send pulses in succession.
The WearTrack system augments reality applications using a single ultrasonic beacon placed on one of the user's finger and three detectors arranged in a fixed relationship to each other on a head set. The system also requires an inertial head orientation module that uses piezoelectric gyroscopes, and solid-state accelerometers and magnetometers. The system needs to be triggered by a unique IR code from the headset, Foxlin et al., “Weartrack: A selfreferenced head and hand tracker for wearable computers and portable VR, ISWC, pp. 155-162, 2000.